Core Python Programming (2nd Edition)

1.3. Features
Although it has been around for well over fifteen years, some feel that Python is still relatively new to
the general software development industry. We should, however, use caution with our use of the word
"relatively," as a few years seem like decades when developing on "Internet time."
When people ask, "What is Python?" it is difficult to say any one thing. The tendency is to want to blurt
out all the things that you feel Python is in one breath. Python is (fill-in-the-blanks here). Just what are
some of those features? For your sanity, we will elucidate each here ... one at a time.
1.3.1. High Level
It seems that with every generation of languages, we move to a higher level. Assembly was a godsend
for those who struggled with machine code, then came FORTRAN, C, and Pascal, which took computing
to another plane and created the software development industry. Through C came more modern
compiled languages, C++ and Java. And further still we climb, with powerful, system-accessible,
interpreted scripting languages like Tcl, Perl, and Python.
Each of these languages has higher-level data structures that reduce the "framework" development time
that was once required. Useful types like Python's lists (resizeable arrays) and dictionaries (hash tables)
are built into the language. Providing these crucial building blocks in the core language encourages their
use and minimizes development time as well as code size, resulting in more readable code.
Because there is no one standard library for heterogeneous arrays (lists in Python) and hash tables
(Python dictionaries or "dicts" for short) in C, they are often reimplemented and copied to each new
project. This process is messy and error prone. C++ improves the situation with the standard template
library, but the STL can hardly compare to the simplicity and readability of Python's built-in lists and
dicts.
1.3.2. Object Oriented
Object-oriented programming (OOP) adds another dimension to structured and procedural languages
where data and logic are discrete elements of programming. OOP allows for associating specific
behaviors, characteristics, and/or capabilities with the data that they execute on or are representative
of. Python is an object-oriented (OO) language, all the way down to its core. However, Python is not just
an OO language like Java or Ruby. It is actually a pleasant mix of multiple programming paradigms. For
instance, it even borrows a few things from functional languages like Lisp and Haskell.
1.3.3. Scalable
Python is often compared to batch or Unix shell scripting languages. Simple shell scripts handle simple
tasks. They may grow (indefinitely) in length, but not truly in depth. There is little code-reusability and
you are confined to small projects with shell scripts. In fact, even small projects may lead to large and
unwieldy scripts. Not so with Python, where you can grow your code from project to project, add other
new or existing Python elements, and reuse code at your whim. Python encourages clean code design,
high-level structure, and "packaging" of multiple components, all of which deliver the flexibility,
consistency, and faster development time required as projects expand in breadth and scope.
The term "scalable" is most often applied to measuring hardware throughput and usually refers to
additional performance when new hardware is added to a system. We would like to differentiate this
comparison with ours here, which tries to reflect the notion that Python provides basic building blocks on